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Fruits and berries distributor launched a connected planning process in Anaplan

Client
Distributor of exotic fruits, berries and vegetables
Industry
Distribution and Logistics
Functional area
Sales and Operations Planning (S&OP)
Solution
Anaplan
Fruits and berries distributor launched a connected planning process in Anaplan

“Thanks to the Anaplan-based solution launched, the company is able to quickly manage individual managers' sales results at the sales position and customer level, something that was previously hard to perform. Now sales forecasting is developed using artificial intelligence capabilities. We create and manage plans on a cutting-edge platform where we now track sales goals in real time. We built Ferrari in connected planning.”

Director of Information Technology Services
01
BUSINESS CHALLENGE

A large distributor of exotic fruits and berries is selling its products in the largest national retail chains, as well as using the HORECA channel. Constant exponential growth of business volumes, intensified competition and the consequences of lockdown have challenged the company to accelerate, increase efficiency and accuracy in its sales and operational planning.

The high demands of the premium consumer segment on product quality, the conditions of chain retailers on the level of service, and the short life cycle of the product formed the profile of the required changes in internal processes and technological planning tools. The pre-existing process could not handle the ever-changing realities of business, thereby creating challenges for business development in a complex pandemic environment. The process was supported by dozens of disparate Excel files, and a local system, originally designed to support ERP processes, that was fine-tuned to the company’s needs.

The clients’ team decided to look for a platform that would automate and at the same time optimize the sales and operations planning (S&OP) process with the ability to perform rolling planning with quarterly updates. It was also necessary to significantly improve the quality of developing and working with the forecast, namely to increase details to SKU level, to better forecast both regular and seasonal sales, to set up a user-friendly interface for adjusting and approving the forecast.

A large distributor of exotic fruits and berries is selling its products in the largest national retail chains, as well as using the HORECA channel. Constant exponential growth of business volumes, intensified competition and the consequences of lockdown have challenged the company to accelerate, increase efficiency and accuracy in its sales and operational planning.

The high demands of the premium consumer segment on product quality, the conditions of chain retailers on the level of service, and the short life cycle of the product formed the profile of the required changes in internal processes and technological planning tools. The pre-existing process could not handle the ever-changing realities of business, thereby creating challenges for business development in a complex pandemic environment. The process was supported by dozens of disparate Excel files, and a local system, originally designed to support ERP processes, that was fine-tuned to the company’s needs.

The clients’ team decided to look for a platform that would automate and at the same time optimize the sales and operations planning (S&OP) process with the ability to perform rolling planning with quarterly updates. It was also necessary to significantly improve the quality of developing and working with the forecast, namely to increase details to SKU level, to better forecast both regular and seasonal sales, to set up a user-friendly interface for adjusting and approving the forecast.

02
SOLUTION

To automate the sales & operations planning (S&OP) process, the Planingo team implemented Anaplan platform with built-in Machine Learning algorithms to generate operational and long-term sales forecasts:

  • Thanks to Anaplan, the sales & operations planning process was re-examined, organized and automated, being unique for the company’s business.
  • As part of the project, a model for planning a prospective annual sales budget and its further disaggregation to the operational level with the allocation of objectives to the level of specific sales managers, price categories and customers was launched. It was just the project’s month 6 when the company generated a new annual budget all the way through in Anaplan. A gap management process was implemented, which shifted the focus to managing the difference between the strategic goals and the operational plan numbers.
  • A unique intraday planning « exchange » layer was created to improve product turnover and speed decision-making. This solution enabled intraday distribution of unsold volumes by sales managers to customers to reduce losses and maximize sales results, as well as increasing the speed of interaction between the sales and purchasing departments.
  • The company implemented new operational planning processes and switched over to a lower level of forecasting. Forecasts developed with Machine Learning algorithms and 6 statistical models are available for development. The planning manager independently selects the forecast by comparing the accuracy of the approaches used. As part of the project, a data hub (data warehouse), a separate model for data preloading, cleaning, verification and enrichment, was created. The data warehouse is integrated with the company’s accounting and transactional systems and provides a single “source of truth” in planning.
  • The Competence Center was created, which allows the company to develop the solution independently after its launch, which resulted in great savings on external consultants’ services.

To automate the sales & operations planning (S&OP) process, the Planingo team implemented Anaplan platform with built-in Machine Learning algorithms to generate operational and long-term sales forecasts:

  • Thanks to Anaplan, the sales & operations planning process was re-examined, organized and automated, being unique for the company’s business.
  • As part of the project, a model for planning a prospective annual sales budget and its further disaggregation to the operational level with the allocation of objectives to the level of specific sales managers, price categories and customers was launched. It was just the project’s month 6 when the company generated a new annual budget all the way through in Anaplan. A gap management process was implemented, which shifted the focus to managing the difference between the strategic goals and the operational plan numbers.
  • A unique intraday planning « exchange » layer was created to improve product turnover and speed decision-making. This solution enabled intraday distribution of unsold volumes by sales managers to customers to reduce losses and maximize sales results, as well as increasing the speed of interaction between the sales and purchasing departments.
  • The company implemented new operational planning processes and switched over to a lower level of forecasting. Forecasts developed with Machine Learning algorithms and 6 statistical models are available for development. The planning manager independently selects the forecast by comparing the accuracy of the approaches used. As part of the project, a data hub (data warehouse), a separate model for data preloading, cleaning, verification and enrichment, was created. The data warehouse is integrated with the company’s accounting and transactional systems and provides a single “source of truth” in planning.
  • The Competence Center was created, which allows the company to develop the solution independently after its launch, which resulted in great savings on external consultants’ services.
03
BUSINESS VALUE
  • The annual planning process is automated and switched to a rolling quarterly cycle. The duration of the planning cycle was reduced to 3-5 days.
  • The detailed breakdown of the company’s goals extended from the manager product level to the customer-SKU bundle level. The accuracy of the operating forecast increased by more than 13 percentage points compared to the existing statistical forecast.
  • The time to generate weekly operational forecasts decreased from 4 to 1 hour per sales manager.
  • The annual planning process is automated and switched to a rolling quarterly cycle. The duration of the planning cycle was reduced to 3-5 days.
  • The detailed breakdown of the company’s goals extended from the manager product level to the customer-SKU bundle level. The accuracy of the operating forecast increased by more than 13 percentage points compared to the existing statistical forecast.
  • The time to generate weekly operational forecasts decreased from 4 to 1 hour per sales manager.

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